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We are living during a time, where data is king.  Therefore businesses are pressed to evolve their analytics and measurement practices.  Otherwise, they risk falling behind their more analytically-savvy competitors. Assessing your analytics and measurement maturity now represents a huge opportunity to stay one step ahead in today’s climate.

All analytics maturity models aim to describe the same thing.

While the specific stages may vary, all maturity models aim to describe similar elements. At a high level, analytics maturity models typically follow a similar progression.  They aspire to provide a roadmap for enhancing analytical capabilities over time. They all look to compare current capabilities against a rubric or list of best-in-class practices. By assessing such capabilities and identifying areas for improvement, organizations can develop a roadmap for becoming more data-driven.

Not Everything and Everyone will be at the Same Stage

It’s important to note that not every department or every team within an organization will be at the same stage of analytics and measurement maturity. Different teams, departments, and/or product areas may have highly varying levels of analytical capability and may be on seemingly independent roadmaps and timelines in terms of how (or if) they’re looking to evolve. 

It’s critical to understand these differences for several key reasons.  To effectively assess an organization’s overall level of maturity, identify individual areas for improvement, and attempt to corral the organization into a holistic plan for evolving its analytics and measurement capabilities.

The Six Stages to Consider Within Measurement

The image below outlines what can generally be thought of as six potential “stages” an organization should consider and potentially assess its analytics against, with increasing levels of maturity and sophistication. The stages represent an amalgamation and augmentation of numerous analytics maturity models from sources such as Gartner, Ovative, Adverity, etc. 

As opposed to addressing analytics maturity in its entirety, here the focus is specifically around measurement. Therefore each stage is evaluated against the following:

  • Organization Structure – Degree to which an organization is structured in order to support analytics and measurement activities
  • Measurement & Metrics – Data available, frameworks deployed, and the resulting metrics/KPIs that comprise decisioning
  • Customer Journey – Process by which customers interact with an organization.  This typically includes key touch-points and pain points along the way to conversion
  • Methodologies & Tools – Analytical toolkit used to support more advanced and diverse measurement methodologies.  Oftentimes, this includes approaches such as Marketing Mix Modeling (MMM), Multi-Touch Attribution (MTA), and incrementality testing.

Bridging the Gap

There is no doubt that evolving one’s analytics and measurement practice to address existing gaps takes time.  However focusing on key best practices below can help build a roadmap, accelerate the process, and drive success.

Align to Business Outcomes: Correlate your analytics directly to your business objectives and outcomes. Whether it’s building a basic OKR framework, navigating how to triangulate multiple, advanced measurement outputs, or aggressively Scale Test into a channel, start by clearly defining the business goals that you want to achieve and then ensure that your analytics roadmap is aligned to them.

Build a Data-Driven Culture: The industry moves quickly and often dramatically. It’s important to build a data-driven culture across the organization, not just within obvious departments such as Data Science. Everyone in the org must understand the value chain of data and feel empowered to use data to make decisions.

Start Small: Start with a small, manageable project and iterate based on what you learn to demonstrate the value of analytics to the organization. Slowly build a coalition; gaining momentum is a critical aspect to forcing change.

Measure and Track Progress: Analytics is a process, not an end goal. Therefore, continuously measure and track progress towards your business objectives.  Review and update your analytics processes, methodologies, and roadmap for quality assurance regularly.

How Transparent Partners Can Help

As a starting point, Transparent deploys a “Measurement Maturity Survey.” Its purpose is to force organizations to take an honest look at their analytics and measurement capabilities. Think of this as the ultimate “thought starter”.  Doing so enables a much more thorough current state assessment of one’s analytics and measurement to identify gaps and areas for improvement. Transparent then works closely with key stakeholders to carefully craft a future state roadmap to evolve analytics and measurement, enable capabilities, and unlock business value.

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